face anti-spoofing based on color texture analysis

19 Nov 2015  ·  Zinelabidine Boulkenafet, Jukka Komulainen, Abdenour Hadid ·

Research on face spoofing detection has mainly been focused on analyzing the luminance of the face images, hence discarding the chrominance information which can be useful for discriminating fake faces from genuine ones. In this work, we propose a new face anti-spoofing method based on color texture analysis. We analyze the joint color-texture information from the luminance and the chrominance channels using a color local binary pattern descriptor. More specifically, the feature histograms are extracted from each image band separately. Extensive experiments on two benchmark datasets, namely CASIA face anti-spoofing and Replay-Attack databases, showed excellent results compared to the state-of-the-art. Most importantly, our inter-database evaluation depicts that the proposed approach showed very promising generalization capabilities.

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Results from the Paper

Task Dataset Model Metric Name Metric Value Global Rank Result Benchmark
Face Anti-Spoofing MSU-MFSD Color LBP Equal Error Rate 10.8% # 3
Face Anti-Spoofing Replay-Attack YCbCr+HSV-LBP EER 0.40 # 3
HTER 2.90 # 3


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